Mike Lawson, host of
CU Broadcast, states "
Paul not only provides great insight on this information evolution, but he also gives us a couple of eye-popping examples of how credit unions are benefiting from this customized content. Really good stuff here."

A common misunderstanding with data analytics is how and when the various “tools” are used. Many think that a great data visualization tool (e.g. Tableau) will solve all of an organization’s problems. Often overlooked, however, are the many steps it takes for an organization to get from data ground zero to becoming completely analytically proficient. When it comes to data management and analytics, the order in which you introduce new tools is extremely important. In order to make each step up the analytics curve effective as the last, credit unions must consider the following steps:

Data Access – The first step in an analytics strategy is simply getting access to the data necessary for analytics. Although this may seem like a fairly easy task, credit unions may find it difficult to get access to the data they are looking for. It may be due to the level of skill needed to the extract the data or due to a vendor’s unwillingness to provide the data. Whatever the challenge might be, data access is an extremely important task in becoming analytically proficient and will need to be tackled right away.